Upscaling petrophysical well log properties and summaries with GeolOil

GeolOil has a dedicated module to upscale petrophysical properties from LAS
well logs. (Think of upscaling as a summary or equivalent value, similar
to an average). The module can compute upscaled values for intensive and
extensive properties, as well as other special cases.

An Intensive property, is a physical property for which its summary,
upscaled or representative single value does not depend upon the sample size
or overall volume. Classical examples of intensive properties are density,
porosity, and water saturation. Extensive properties inherently
depend upon the sample size or volume.

Examples of extensive properties are equivalent hydrocarbon column (depends
upon the zone's thickness: the thicker, the larger), and bulk volume of water in
a zone. Likewise, reservoir properties like net-reservoir thickness, net-sand
thickness, and net-pay can be considered as special cases of extensive upscaling
computed on the summation of indicator lithotypes. Generally speaking, average
types are related to intensive upscaling, and totals or nets are related to
extensive upscaling.

GeolOil allows to define an unlimited amount of upscaling types. Each upscaling
will have its own combination of computation type, lithology or facies definition,
the zones, layers or vertical cells where it will be computed, the resulting
upscaled values or summaries, as well as the creation of a staircase
style log curve to display and compare the results against the original log curve.
Typical reservoir properties computed by GeolOil are:

The figure below shows the main upscaling list panel, with SW upscaling highlighted

The figure below shows the upscaling processing panel.
Notice that an intensive upscaling was specified for SW.

GeolOil allows to define lithology types in several ways. There can be available
indicator flag curves for lithologies and facies, or the user can define a lithology
through a series of filters and cutoffs. For instance, gross rocks should not be
filtered, so the whole column should be accepted. Likewise, lithologies like
clean sandstones should be filtered by a low Gamma Ray curve signal (for example,
GR below 65 units API) and photoelectric factor of around 1.9 B/E units.
Limestones should be filtered by PEF curve values around 5 B/E units, and so forth
for other lithologies.

The processing panel should have filled as much as possible, all the
relevant curve numbers for the requested upscaling computation. For example,
if the upscaling of water saturation on gross rocks is desired, the user must
specify the curve numbers both for porosity and water saturation (since correct
SW upscaling depends not only on SW itself, but also on its porosity). Also,
the target property (row item 0) must has the same water saturation curve number.
This is the way GeolOil will know to use the right equations to upscale water
saturation.

Treatment of outliers can be specified in the processing panel. For instance,
if the user needs to upscale porosity, what is the best processing treatment
that has to be done for negative values?. Clearly, negative values for porosity
should not be allowed to enter into the computations. A negative outlier value
might be rejected (discarded and thrown away), or trimmed (converted to a value
like 0.0). The user also has options to discard unreliable depth zone intervals.

The figure below shows the curves and cutoffs filtering panel.

The figure below shows the zonation panel, where curve outputs can be defined and additional zone filters applied

The figure below shows the results panel, where upscaled values are tabulated for each layer or cell zone

The figure below shows the plot of an upscaled SW curve (UPS_SW), shown in black with a staircase steps pattern